output
20062026
most citedObservation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC

10.9k citations

235 papers

cs.CV2026

Elastoformer: Enabling Dynamic Adaptivity via Elastic Model Transformation

Sudaksh Kalra, Dolly Sapra

EdgeAI systems are increasingly employing computer vision applications to enable intelligent, on-device decision-making in real-time. However, these deployments face highly dynamic…

cs.IR2026

An Epistemic Position-Based Click Model: From Interactions to Epistemic Distributions of Relevance and Bias

Oscar Rolando Ramirez Milian, Harrie Oosterhuis

User interactions with rankings are affected by both items' relevances and display positions. Accordingly, click probabilities are often modeled as a product of relevance and posit…

cs.LG2026

Exposure-Based Reinforcement Learning to Rank

Harrie Oosterhuis, Rolf Jagerman, Zhen Qin +1

Reinforcement learning (RL) methods for learning-to-rank (LTR) can optimize (almost) any ranking goal, e.g., from precision or discounted cumulative gain to fairness-of-exposure or…

cs.DC2026

EcoKube: Simulating Carbon-Aware Scheduling Policies in Heterogeneous Edge-Cloud Environments

Gonçalo Ferreira, Shashikant Ilager

Energy demand from cloud and edge computing is rising rapidly, with AI workloads further intensifying electricity use and associated carbon emissions. In hybrid edge-cloud settings…

cs.IR2026

The Powerless Noise: How Experimental Settings Shape the Reported Power of Noise

Michał Mazuryk, Fleur Dolmans, Louis Gehringer +3

Recent work has suggested that adding irrelevant documents to the input of retrieval-augmented generation (RAG) systems can improve question-answering performance, a phenomenon ref…

cs.IR2026

Search for Coverage: Learning Coverage-Aware Retrieval with Augmented Sub-Question Answerability

Jia-Huei Ju, Eugene Yang, Trevor Adriaanse +2

Long-form Retrieval-Augmented Generation (RAG) brings the challenge of coverage-based ranking, because ranking methods must ensure the inclusion of comprehensive relevant nuggets (…